Europe is experiencing an extraordinary acceleration in artificial intelligence innovation. From powerful language models to automation tools reshaping entire industries, the continent is positioning itself as a global tech force. But while the spotlight is on startups revolutionizing logistics, finance, and enterprise software, another sector is being quietly ignored. Despite its massive potential and societal importance, the AI boom is leaving femtech behind.
This growing gap between cutting-edge AI and women-focused technology isn’t just a funding oversight it’s a structural issue that highlights who gets prioritized in innovation, and who doesn’t.
The Promise of Femtech And Why It’s Being Ignored
Femtech, short for “female technology,” includes digital health products, services, and platforms designed specifically for women’s health and well-being. Think fertility tracking apps, menopause monitoring tools, smart wearables for hormonal health, and AI-powered diagnostics for gynecological conditions.
By all accounts, femtech is a booming industry. It has the potential to improve outcomes for millions of women across Europe. Yet the numbers show a stark reality: the AI boom is leaving femtech behind in funding, visibility, and innovation prioritization.
How the Numbers Reveal the Gap
While billions of euros are pouring into general AI startups, femtech ventures are struggling to secure even a fraction of that capital. Across Europe, AI has become the darling of venture capital. It attracts attention from governments, private equity, and corporate partners. Investors are racing to back the next foundational model or productivity tool. But femtech, even with strong user engagement and social relevance, remains underfunded.
What this reveals is a deeper issue: as AI takes off, certain sectors are left in the dust. And sadly, when it comes to tech created by and for women, the AI boom is leaving femtech behind far too often.
Why Is Femtech Being Left Behind?
The issue isn’t just financial it’s cultural, structural, and systematic. Several key reasons explain why the AI boom is leaving femtech behind:
1. Investment Bias Toward Scalable, Male-Dominated Tech
VCs often chase scale they’re looking for products that appeal to a broad audience, often by default meaning “general-purpose.” Unfortunately, femtech doesn’t always fit that mold. Solutions that address menstrual cycles, reproductive health, or menopause are seen as “niche,” despite affecting half the population.
Additionally, the majority of VC decision-makers are male. They may not relate to or understand the value of femtech products, which leads to underestimation and underinvestment.
2. Femtech Is Seen as High-Risk and Over-Regulated
Building medical or health-related technology often involves more regulation, clinical testing, and ethical scrutiny. This makes femtech “slower” in investor terms. AI startups in other spaces can often launch quickly, iterate fast, and scale with fewer barriers.
As AI funding surges, investors prefer lighter, quicker returns which often excludes femtech from serious consideration. That’s another reason the AI boom is leaving femtech behind: it simply doesn’t fit the fast-growth narrative.
3. Lack of Representation in Tech Leadership
Most AI ventures are led by male founders. Most femtech startups, on the other hand, are launched by women who deeply understand the problems they’re solving. But the tech world still struggles with gender representation. This lack of diversity extends to pitch rooms, incubators, and media coverage.
Because of that, femtech rarely benefits from the same amplification that AI startups enjoy. While generative AI companies are headlining conferences, femtech solutions are buried in breakout sessions. The AI boom is leaving femtech behind, in part, because it’s still a boys’ club at the top.
4. Data Gaps in Women’s Health
AI thrives on data massive amounts of it. But in women’s health, especially around reproductive and hormonal conditions, there’s a historical lack of reliable data. From clinical trials that excluded women to decades of under-researched conditions like endometriosis, the result is a weak foundation for AI models to learn from.
Femtech startups often have to build their own datasets from scratch, which is time-consuming and expensive. This further delays development and scares off investors who want plug-and-play solutions. Again, the AI boom is leaving femtech behind because the infrastructure just isn’t there yet.
The Missed Opportunity
Ignoring femtech isn’t just a disservice to women it’s a bad business decision. The global femtech market is projected to reach over $60 billion by the end of this decade. That includes fertility, contraception, maternal health, chronic condition tracking, and more.
With an aging population, delayed pregnancies, and growing focus on personalized healthcare, the need for femtech is skyrocketing. Yet the funding isn’t following. While Europe throws billions at AI chatbots and automation startups, femtech startups that could improve women’s quality of life are left to bootstrap their way forward.
What Femtech Could Do with Better AI Support
Here’s the irony: femtech and AI aren’t mutually exclusive. In fact, combining the two could revolutionize women’s healthcare. Imagine:
- AI-powered cycle prediction tools that adapt based on mood, sleep, and stress data
- Machine learning algorithms that detect early signs of reproductive diseases
- Voice-enabled menopause assistants that offer real-time, science-backed support
- AI-based mental health diagnostics tailored for postpartum depression or PCOS-related anxiety
The possibilities are vast. Yet because the AI boom is leaving femtech behind, these ideas stay on whiteboards instead of becoming market-ready products.
A New Approach to Tech Equity
To correct course, Europe needs to reframe how it values tech innovation. Rather than asking “what can scale fastest?” or “what sounds futuristic?”, funders and policymakers should be asking: Who benefits from this tech? Who is being left behind?
The AI boom can and should include femtech but it won’t happen without deliberate change. That includes:
- Diversifying investment panels
- Offering grants or public funding for femtech R&D
- Building AI models that reflect women’s health realities
- Highlighting femtech success stories in mainstream media
- Promoting partnerships between femtech startups and AI research labs
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